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Data Analysis, Machine Learning and Knowledge Discovery de Myra Spiliopoulou

Data Analysis, Machine Learning and Knowledge Discovery: Studies in Classification, Data Analysis, and Knowledge Organization

Editat de Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning
en Limba Engleză Paperback – 9 dec 2013
Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​
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Specificații

ISBN-13: 9783319015941
ISBN-10: 331901594X
Pagini: 430
Ilustrații: XXI, 470 p. 120 illus., 32 illus. in color.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.69 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Classification, Data Analysis, and Knowledge Organization

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

AREA Statistics and Data Analysis: Classifcation, Cluster Analysis, Factor Analysis and Model Selection.- AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks.- AREA Data Analysis and Classification in Marketing.- AREA Data Analysis in Finance.- AREA Data Analysis in Biostatistics and Bioinformatics.- AREA Interdisciplinary Domains: Data Analysis in Music, Education and Psychology.- LIS Workshop: Workshop on Classification and Subject Indexing in Library and Information Science.

Recenzii

From the book reviews:
“The book is organized in seven parts … . The book is a very interesting collection of papers describing various approaches of data mining and machine learning on aspects from bioinformatics to music classification. It is an excellent addition to the field and it can be used as starting point for projects from undergraduate to post-graduate level.” (Irina Ioana Mohorianu, zbMATH, Vol. 1301, 2015)

Textul de pe ultima copertă

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​

Caracteristici

Focus on the commonalities concerning data analysis in computer science and in statistics Emphasis on both methods (statistical analysis and machine learning) and applications (marketing, finance, bioinformatics, musicology, psychology) Presentation of general methods and techniques that can be applied to a variety of fields? Includes supplementary material: sn.pub/extras